Computational framework for a systematic investigation of anionic redox process in Li-rich compounds

Abstract

Anionic redox processes play a key role in determining the accessible capacity and cycle life of Li-rich cathode materials for batteries. We present a framework for investigating the anionic redox processes based on data readily available from standard DFT calculations. Our recipe includes a method of classifying different anionic species, counting the number of species present in the structure and a preconditioning scheme to promote anionic redox. The method is applied to a set of LixMnO3 (1 ≤ x ≤2) structures, with cationic disorder, to identify the evolution of anionic redox processes during cycling. Additionally, we investigate how different choices of exchange-correlation functionals affect the formation of anionic redox species. The preconditioning of the structures is shown to promote the formation of peroxo-like species. Furthermore, the choice of exchange-correlation functional has a large impact on the type of anionic redox species present, and thus care must be taken when considering localization in anionic species.